EMR-Linked Biobank for Translational Genomics

用于转化基因组学的 EMR 关联生物库

• 批准号: 9515974
• 负责人: Marc S. Williams
• 金额: $ 87.12万
• 依托单位: GEISINGER CLINIC
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9515974
• 关键词: Adult; Algorithms; Ambulatory Care; Area; Attitude; Candidate Disease Gene; Caring; Catchment Area; Child; Clinical; Communication; Computerized Medical Record; Consent; County; Cystic Fibrosis Transmembrane Conductance Regulator; Data; Deposition; Development; Diagnosis; Disease; Dreams; Economic Models; Ecosystem; Electronic Health Record; Electronic Medical Records and Genomics Network; Ensure; Environment; Familial Hypercholesterolemia; Familial disease; Family; Family member; Foundations; Funding Opportunities; Generations; Genes; Genomic medicine; Genomics; Genotype; Geography; Goals; Group Practice; Health; Health Insurance; Health care facility; Health system; Healthcare; Healthcare Systems; Individual; Information Systems; Institute of Medicine (U.S.); Integrated Health Care Systems; Knowledge; Lead; Leadership; Learning; Link; Lipids; Machine Learning; Medical; Medicine; Methods; Outcome Study; Participant; Patient Care; Patients; Pennsylvania; Phase; Phenotype; Physicians; Play; Population; Process; Prognostic Factor; Provider; Public Health; Recommendation; Research; Research Infrastructure; Research Personnel; Resources; Risk; Role; Rural; Rural Population; Safety; Severity of illness; Site; Strategic Planning; System; Techniques; Testing; Treatment outcome; United States; Validation; Variant; base; biobank; case finding; chronic rhinosinusitis; clinical care; clinical practice; clinically relevant; density; design; epidemiology study; experience; gene environment interaction; genetic association; genetic epidemiology; genetic variant; genotyped patients; implementation research; implementation strategy; innovation; inpatient service; interest; meetings; novel; novel strategies; personalized health care; phase 3 study; phenome; population based; programs; public health relevance; screening; tool; trait; translational genomics; treatment response

 DESCRIPTION (provided by applicant): Medical care informed by genomic information is beginning to move into clinical practice. The Electronic Medical Records and Genomics (eMERGE) network through its initial phases has provided much of the groundwork for this transformation. The Geisinger Health System project, "EMR-Linked Biobank for Translational Genomics" intends to build on the knowledge and experience from eMERGE phase II to accelerate discovery and implementation while expanding our understanding of the sociocultural implications of genomics in medicine. We will accomplish this goal through three specific aims: 1) Use existing biospecimens, genotype and sequence data and EMR-generated phenotypes for discovery in the proposed disorders: familial hypercholesterolemia and chronic rhinosinusitis, 2) Develop and test approaches for implementation of genomic information in clinical practice, 3) Explore, develop and implement novel approaches for family-centered communication around clinically relevant genomic results. We currently have over 60,000 patients broadly consented for research with a large and increasing proportion consented for return of results and deposition in the electronic health record. Over 18,000 patients are genotyped on high density platforms. Our two proposed phenotypes, familial hypercholesterolemia (FH) and chronic rhinosinusitis (CRS) were chosen because both conditions have a significant public health impact in the United States, but they are also ideally suited to the specific aims of the project. They provide opportunities for innovation and extension of current eMERGE methods. While many of these innovations will take advantage of the sequencing done as part of the project, there are several other areas emphasized in the funding opportunity that will broaden the scope of eMERGE research. One of the areas of emphasis for eMERGE III is exploring the familial return of actionable results. FH is well suited to this, as the current clinical recommendation is cascade testing of family members for all diagnosed patients. Currently this relies on the patient to contact at risk family members, but this is less than optimal. We will explore this issue using qualitative and quantitative methods and use the results to design and test novel family communication strategies. Gene-environment interactions play an important role in the development and severity of disease. These are very difficult to study. We propose novel approaches that leverage the assets of Geisinger Health System and the eMERGE Network to develop and apply methods to extend existing projects that study the impact of environment on CRS. This would include the first large scale environment-wide association studies (EWAS). Finally, we propose to lead efforts to apply the tools of economic modeling and analysis to eMERGE projects to begin to quantify the value of implementation of genomic medicine in the US healthcare system. These proposed innovations will magnify the already significant impact that the eMERGE program has had in moving genomic medicine from a dream to a reality.

 描述（由申请人提供）：基于基因组信息的医疗保健正开始进入临床实践。电子病历和基因组学 (eMERGE) 网络在其初始阶段为这一转变奠定了基础。 Geisinger 卫生系统项目“用于转化基因组学的 EMR 关联生物库”旨在以 eMERGE 第二阶段的知识和经验为基础，加速发现和实施，同时扩大我们对医学基因组学的社会文化影响的理解。我们将通过三个具体目标来实现这一目标：1) 使用现有的生物样本、基因型和序列数据以及 EMR 生成的表型来发现所提出的疾病：家族性高胆固醇血症和慢性鼻窦炎，2) 开发和测试在临床实践中实施基因组信息的方法，3) 围绕临床相关基因组结果探索、开发和实施以家庭为中心的沟通新方法。目前，我们有超过 60,000 名患者广泛同意进行研究，其中越来越多的患者同意返回结果并存入电子健康记录。超过 18,000 名患者在高密度平台上进行了基因分型。选择我们提出的两种表型，即家族性高胆固醇血症 (FH) 和慢性鼻窦炎 (CRS)，是因为这两种疾病对美国的公共卫生有重大影响，但它们也非常适合该项目的具体目标。它们为当前 eMERGE 方法的创新和扩展提供了机会。虽然其中许多创新将利用作为项目一部分完成的测序，但资助机会中还强调了其他几个领域，这将扩大 eMERGE 研究的范围。 eMERGE III 的重点领域之一是探索可行结果的家庭回报。 FH 非常适合这一点，因为目前的临床建议是对所有确诊患者的家庭成员进行级联检测。目前，这依赖于患者联系有风险的家庭成员，但这并不是最佳选择。我们将使用定性和定量方法探讨这个问题，并利用结果来设计和测试新颖的家庭沟通策略。基因-环境相互作用在疾病的发展和严重程度中发挥着重要作用。这些都是非常难研究的。我们提出了新的方法，利用 Geisinger Health System 和 eMERGE Network 的资产来开发和应用方法来扩展研究环境对 CRS 影响的现有项目。这将包括首次大规模全环境关联研究（EWAS）。最后，我们建议带头将经济建模和分析工具应用于 eMERGE 项目，以开始量化在美国医疗保健系统中实施基因组医学的价值。这些拟议的创新将放大 eMERGE 计划在将基因组医学从梦想变为现实方面已经产生的重大影响。